2 Metagenome Analysis
61
To progress from piling up a rather static repertoire of gene inventories more information about the expression of the genes, with respect to different sampling sites
and environmental conditions, is needed. Although, still in an early phase metatranscriptomics (Poretsky et al. 2005, Bailly et al. 2007) and metaproteomics (Ram
et al. 2005, Wilmes and Bond 2006) are becoming increasingly visible and promise
insights into the dynamics and regulation of genes in naturally occurring microbial communities. In a recent example Frias-Lopez et al. (Frias-Lopez et al. 2008)
investigated gene expression in ocean surface waters by cDNA pyrosequencing. In
addition to identifying expressed genes from key metabolic pathways, the study
detected a significant amount of highly expressed hypothetical genes. These genes
were most probably involved in the specific adaptation of the organisms and should
be primary targets for further functional assessment.
To transfer the current flood of metagenomic data into biological knowledge,
data generation and storage need to be organised and standardised to handle the
sequences, genomes, genes and predicted metabolic functions and relate them to the
environment that is being analysed (DeLong and Karl 2005, Lombardot et al. 2006,
Markowitz 2007). The Genomic Standards Consortium (GSC) has been recently
established to work on a richer description of our complete collection of genomes
and metagenomes (Field et al. 2007, 2008). The Minimum Information about a
Metagenome Sequence (MIMS) initiative intends to standardise contextual data
acquisition so that investigators are required to anchor their metagenomes in space
and time by providing a minimum of information including GPS coordinates plus
depth/altitude and sampling time (see http://gensc.org). More information about
the physical-chemical characteristics of the samples is needed so that genomic
features can be correlated with habitat properties. This would also allow organismspecific adaptations to be identified and the role and impact of organisms on the
environment to be assessed. To complement missing environmental information
and to obtain a dynamic picture of the stability of the ecosystem under investigation, in situ measurements can be complemented by global data layers. An initial
approach aimed at integrating (meta)genomic information with interpolated habitat
parameters from global ocean data layers is already available (see www.megx.net;
Lombardot et al. 2006). If this approach is developed further, it might be possible to overlay functional diversity, metabolic pathways and phylogenetic diversity
upon physical, chemical and biological data to map microbial features onto marine
provinces.
To allow sound comparisons between the different metagenomic investigations standardization of the processing pipeline is another aspect that is crucial.
Cyberinfrastructures like the CAMERA project in the marine field will be helpful
in this respect by processing a significant portion of the data. Raes et al. (Raes et al.
2007) have proposed MINIMESS, the MINImal Metagenome Sequence analysis
Standard, where basic parameters for assembly, species and functional composition
and coverage as well as biological and technical factors need to be documented for
each metagenome. Such efforts needs to be merged and made transparent to the
data providers and biologists. It will be a major community effort to work on the
integrity and quality of our ever growing metagenomic inventories to improve our
61
To progress from piling up a rather static repertoire of gene inventories more information about the expression of the genes, with respect to different sampling sites
and environmental conditions, is needed. Although, still in an early phase metatranscriptomics (Poretsky et al. 2005, Bailly et al. 2007) and metaproteomics (Ram
et al. 2005, Wilmes and Bond 2006) are becoming increasingly visible and promise
insights into the dynamics and regulation of genes in naturally occurring microbial communities. In a recent example Frias-Lopez et al. (Frias-Lopez et al. 2008)
investigated gene expression in ocean surface waters by cDNA pyrosequencing. In
addition to identifying expressed genes from key metabolic pathways, the study
detected a significant amount of highly expressed hypothetical genes. These genes
were most probably involved in the specific adaptation of the organisms and should
be primary targets for further functional assessment.
To transfer the current flood of metagenomic data into biological knowledge,
data generation and storage need to be organised and standardised to handle the
sequences, genomes, genes and predicted metabolic functions and relate them to the
environment that is being analysed (DeLong and Karl 2005, Lombardot et al. 2006,
Markowitz 2007). The Genomic Standards Consortium (GSC) has been recently
established to work on a richer description of our complete collection of genomes
and metagenomes (Field et al. 2007, 2008). The Minimum Information about a
Metagenome Sequence (MIMS) initiative intends to standardise contextual data
acquisition so that investigators are required to anchor their metagenomes in space
and time by providing a minimum of information including GPS coordinates plus
depth/altitude and sampling time (see http://gensc.org). More information about
the physical-chemical characteristics of the samples is needed so that genomic
features can be correlated with habitat properties. This would also allow organismspecific adaptations to be identified and the role and impact of organisms on the
environment to be assessed. To complement missing environmental information
and to obtain a dynamic picture of the stability of the ecosystem under investigation, in situ measurements can be complemented by global data layers. An initial
approach aimed at integrating (meta)genomic information with interpolated habitat
parameters from global ocean data layers is already available (see www.megx.net;
Lombardot et al. 2006). If this approach is developed further, it might be possible to overlay functional diversity, metabolic pathways and phylogenetic diversity
upon physical, chemical and biological data to map microbial features onto marine
provinces.
To allow sound comparisons between the different metagenomic investigations standardization of the processing pipeline is another aspect that is crucial.
Cyberinfrastructures like the CAMERA project in the marine field will be helpful
in this respect by processing a significant portion of the data. Raes et al. (Raes et al.
2007) have proposed MINIMESS, the MINImal Metagenome Sequence analysis
Standard, where basic parameters for assembly, species and functional composition
and coverage as well as biological and technical factors need to be documented for
each metagenome. Such efforts needs to be merged and made transparent to the
data providers and biologists. It will be a major community effort to work on the
integrity and quality of our ever growing metagenomic inventories to improve our